1st Joint Commission 2 and IGFS Meeting
International Symposium on
Gravity, Geoid and Height Systems 2016

September 19-23, 2016
Thessaloniki, Greece

Validation of time-variable gravity field products with globally distributed in situ ocean bottom pressure observations

19/09/2016 | 16:30 | Session 1: Current and future satellite gravity missions

Author(s):

Lea Poropat, Inga Bergmann-Wolf, Henryk Dobslaw and Frank Flechtner

Abstract

Time variable global gravity field models that are processed by different research institutions all across Europe are currently compared and possibly subsequently combined within the "European Gravity Field Service for Improved Emergency Management (EGSIEM)" project founded by the European Union. To objectively assess differences between the results from different groups, and also to evaluate the impact of changes in the data processing at an individual institution in preparation of a new data release, a validation of the final GRACE gravity fields against independent observations is required.

For such a validation, we apply data from a set of globally distributed ocean bottom pressure sensors. We identify outliers, remove instrumental drifts and trends by a quadratic fit, stack time series from re-deployments including the removal of jumps in the time series due to recovery and re-deployment of a sensor, harmonize the time sampling to one hour, and finally eliminate tidal signals using the T_TIDE MATLAB package for classical harmonic analysis. Both GRACE and in situ time-series are subsequently filtered by 3rd order Butterworth bandpass filters in order to focus on selected frequency bands only. The validation typically concentrates on seasonal to interannual signals, but in case of GRACE-based series with daily sampling available from, e.g., Kalman Smoother Solutions, also sub-monthly signal variability can be assessed.

Download the abstract's file:
Abstract Download

Program Search Form

Presentations Search Form (compact)
Sending

Abstracts Download

Download a ZIP file containing all the GGHS2016 abstracts

Pin It on Pinterest

Share This